Identification of core genes and pathways in melanoma metastasis via bioinformatics analysis

Li, Yumei; Li, Bifei; Fan, Chen; Shen, Weiyu; Katanaev, Vladimir L.; Jia, Lee

doi:10.21203/rs.3.rs-39969/v1

Cited by 2 publications

(4 citation statements)

References 35 publications

(36 reference statements)

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“…• Progesterone-mediated oocyte maturation: Li et al 31 concluded that the progesterone-mediated oocyte maturation pathway is involved in melanoma metastasis through bioinformatics analysis; • Cell cycle: Rünger et al 32 demonstrated that regulation of cell cycle checkpoints and DNA repair is responsible for UV-mediated SC; • Activation of NIMA kinases like NEK9, NEK6, and NEK7 is responsible for CDK and PLK1-mediated phosphorylation. 33 Further, the STRING database was used to build the PPI network.…”

Section: Discussionmentioning

confidence: 99%

“… Cell Cycle: G2/M checkpoint pathway and cell cycle regulation for Biocarta analysis; Phosphorylation of Emi1 and activation of NIMA kinases NEK9 , NEK6 , and NEK7 for Reactome; Progesterone-mediated oocyte maturation: Li et al 31 concluded that the progesterone-mediated oocyte maturation pathway is involved in melanoma metastasis through bioinformatics analysis; Cell cycle: Rünger et al 32 demonstrated that regulation of cell cycle checkpoints and DNA repair is responsible for UV-mediated SC; Activation of NIMA kinases like NEK9, NEK6, and NEK7 is responsible for CDK and PLK1 -mediated phosphorylation. 33 …”

Section: Discussionmentioning

confidence: 99%

“…Progesterone-mediated oocyte maturation: Li et al 31 concluded that the progesterone-mediated oocyte maturation pathway is involved in melanoma metastasis through bioinformatics analysis;…”

Section: Discussionmentioning

confidence: 99%

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Screening out molecular pathways and prognostic biomarkers of ultraviolet-mediated melanoma through computational techniques

Hossain,

Ahsan,

Hasan

et al. 2024

Int J Biol Markers

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Purpose Ultraviolet radiation causes skin cancer, but the exact mechanism by which it occurs and the most effective methods of intervention to prevent it are yet unknown. For this purpose, our study will use bioinformatics and systems biology approaches to discover potential biomarkers of skin cancer for early diagnosis and prevention of disease with applicable clinical treatments. Methods This study compared gene expression and protein levels in ultraviolet-mediated cultured keratinocytes and adjacent normal skin tissue using RNA sequencing data from the National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) database. Then, pathway analysis was employed with a selection of hub genes from the protein-protein interaction (PPI) network and the survival and expression profiles. Finally, potential clinical biomarkers were validated by receiver operating characteristic (ROC) curve analysis. Results We identified 32 shared differentially expressed genes (DEGs) by analyzing three different subsets of the GSE85443 dataset. Skin cancer development is related to the control of several DEGs through cyclin-dependent protein serine/threonine kinase activity, cell cycle regulation, and activation of the NIMA kinase pathways. The cytoHubba plugin in Cytoscape identified 12 hub genes from PPI; among these 3 DEGs, namely, AURKA, CDK4, and PLK1 were significantly associated with survival ( P < 0.05) and highly expressed in skin cancer tissues. For validation purposes, ROC curve analysis indicated two biomarkers: AURKA (area under the curve (AUC) value = 0.8) and PLK1 (AUC value = 0.7), which were in an acceptable range. Conclusions Further translational research, including clinical experiments, teratogenicity tests, and in-vitro or in-vivo studies, will be performed to evaluate the expression of these identified biomarkers regarding the prognosis of skin cancer patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Screening out molecular pathways and prognostic biomarkers of ultraviolet-mediated melanoma through computational techniques

Hossain,

Ahsan,

Hasan

et al. 2024

Int J Biol Markers

View full text Add to dashboard Cite

show abstract

“…Phosphorylation of Emi1 and activation of NIMA kinases NEK9, NEK6, NEK7 for Reactome. Progesterone−mediated oocyte maturation: Yumei Li et al concluded that the progesterone−mediated oocyte maturation pathway is involved in melanoma metastasis through bioinformatics analysis [34]. Cell cycle: Thomas M. Runger et al demonstrated that regulation of cell cycle checkpoints and DNA repair is responsible for UV mediated skin cancer [53] [47].…”

Section: Discussionmentioning

confidence: 99%

Identification of molecular pathways and prognostic biomarkers with survival analysis associated with UV-mediated skin cancer by bioinformatics approaches

Rahman

Hossain

Ahsan

et al. 2022

Preprint

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Skin cancer (SC) referred to as cutaneous carcinoma is a serious public health concern on a global scale particularly for those with fair skin. Ultraviolet (UV) radiation causes skin cancer, but the exact mechanism by which occurs and the most effective methods of intervention to prevent it are yet unknown. Using bioinformatic approaches several biomarkers have been identified to determine the severity of skin cancer. This study will use bioinformatics and pharmacology approaches to discover potential biomarkers of SC for early diagnosis, prevention of disease, and therapeutic target identification. This study compared gene expression and protein levels in UV-mediated cultured keratinocytes and adjacent normal skin tissue using RNA sequencing data from the NCBI-GEO database. Then we employed GO and signalling pathway database, selection of hub genes from protein-protein interaction (PPI) network, survival and expression profile, and gene regulatory network analysis to screen potential clinical biomarkers. In the study, we identified 32 shared differentially expressed genes (DEGs) including 19 upregulated genes and 13 downregulated genes by analyzing three different subsets of the GSE85443 dataset. Skin cancer development is related to control of several DEGs through cyclin-dependent protein serine/threonine kinase activity, cell cycle regulation and activation of the NIMA kinase pathways. The cytohubba plugin in Cytoscape identified twelve hub genes from PPI; among these three DEGs namely, AURKA, CDK4, and PLK1 were shown to be significantly associated with survival (p $<$ 0.05) and highly expressed in SC tissues. Transcriptional, post-transcriptional, and protein-chemical also indicates the hub genes bound to several molecules. Further investigation and clinical experiments will be needed to evaluate the expression of these identified biomarkers regarding the prognosis of SC patients.

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Identification of core genes and pathways in melanoma metastasis via bioinformatics analysis

Cited by 2 publications

References 35 publications

Screening out molecular pathways and prognostic biomarkers of ultraviolet-mediated melanoma through computational techniques

Screening out molecular pathways and prognostic biomarkers of ultraviolet-mediated melanoma through computational techniques

Identification of molecular pathways and prognostic biomarkers with survival analysis associated with UV-mediated skin cancer by bioinformatics approaches

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